A census of human RNA-binding proteins

RBProkCNN: Deep learning on appropriate contextual evolutionary information for RNA binding protein discovery in prokaryotes

RNA-binding proteins (RBPs) are central to key functions such as post-transcriptional regulation, mRNA stability, and adaptation to varied environmental conditions in prokaryotes. While the majority of research has concentrated on eukaryotic RBPs, recent developments underscore the crucial involvement of prokaryotic RBPs. Although computational methods have emerged in recent years to identify RBPs, they have fallen short in accurately identifying prokaryotic RBPs due to their generic nature. To bridge this gap, we introduce RBProkCNN, a novel machine learning-driven computational model meticulously designed for the accurate prediction of prokaryotic RBPs. The prediction process involves the utilization of eight shallow learning algorithms and four deep learning models, incorporating PSSM-based evolutionary features. By leveraging a convolutional neural network (CNN) and evolutionarily significant features selected through extreme gradient boosting variable importance measure, RBProkCNN achieved the highest accuracy in five-fold cross-validation, yielding 98.04% auROC and 98.19% auPRC. Furthermore, RBProkCNN demonstrated robust performance with an independent dataset, showcasing a commendable 95.77% auROC and 95.78% auPRC. Noteworthy is its superior predictive accuracy when compared to several state-of-the-art existing models. RBProkCNN is available as an online prediction tool (https://iasri-sg.icar.gov.in/rbprokcnn/), offering free access to interested users. This tool represents a substantial contribution, enriching the array of resources available for the accurate and efficient prediction of prokaryotic RBPs.

Identification of RNA-binding protein genes associated with renal rejection and graft survival

Rejection is one of the major factors affecting the long-term prognosis of kidney transplantation, and timely recognition and aggressive treatment of rejection is essential to prevent disease progression. RBPs are proteins that bind to RNA to form ribonucleoprotein complexes, thereby affecting RNA stability, processing, splicing, localization, transport, and translation, which play a key role in post-transcriptional gene regulation. However, their role in renal transplant rejection and long-term graft survival is unclear. The aim of this study was to comprehensively analyze the expression of RPBs in renal rejection and use it to construct a robust prediction strategy for long-term graft survival. The microarray expression profiles used in this study were obtained from GEO database. In this study, a total of eight hub RBPs were identified, all of which were upregulated in renal rejection samples. Based on these RBPs, the renal rejection samples could be categorized into two different clusters (cluster A and cluster B). Inflammatory activation in cluster B and functional enrichment analysis showed a strong association with rejection-related pathways. The diagnostic prediction model had a high diagnostic accuracy for T cell mediated rejection (TCMR) in renal grafts (area under the curve = 0.86). The prognostic prediction model effectively predicts the prognosis and survival of renal grafts (p < .001) and applies to both rejection and non-rejection situations. Finally, we validated the expression of hub genes, and patient prognosis in clinical samples, respectively, and the results were consistent with the above analysis.

Long non-coding RNAs: roles in cellular stress responses and epigenetic mechanisms regulating chromatin

Most of the genome is transcribed into RNA but only 2% of the sequence codes for proteins. Non-coding RNA transcripts include a very large number of long noncoding RNAs (lncRNAs). A growing number of identified lncRNAs operate in cellular stress responses, for example in response to hypoxia, genotoxic stress, and oxidative stress. Additionally, lncRNA plays important roles in epigenetic mechanisms operating at chromatin and in maintaining chromatin architecture. Here, we address three lncRNA topics that have had significant recent advances. The first is an emerging role for many lncRNAs in cellular stress responses. The second is the development of high throughput screening assays to develop causal relationships between lncRNAs across the genome with cellular functions. Finally, we turn to recent advances in understanding the role of lncRNAs in regulating chromatin architecture and epigenetics, advances that build on some of the earliest work linking RNA to chromatin architecture.

Oncogenic role of RNA-binding protein GNL2 in glioma: Promotion of tumor development through enhancing protein synthesis

RNA-binding proteins (RBPs) are aberrantly expressed in various diseases, including glioma. In the present study, the role and mechanism of RBPs in glioma were investigated. Differentially expressed genes (DEGs) in glioma were screened from public databases and overlapping genes between DEGs and RBPs were selected in a bioinformatics analysis to identify the hub gene. Next, evaluation of expression, survival analysis and cell experiments were performed to examine the impact of the hub gene on glioma. Through bioinformatics analysis, G protein nucleolar 2 (GNL2), programmed cell death 11 (PDCD11) and ribosomal protein S6 (RPS6) were identified as potential biomarkers in glioma prognosis and GNL2 was chosen as the hub gene for further investigation. GNL2 was increased in glioma tissues and related to poor survival outcomes. Cell experiments revealed that GNL2 knockdown inhibited glioma cell growth, migration and invasion. In addition, GNL2 was found to affect the overall protein synthesis of ribosomal protein L11 in glioma cells. In conclusion, GNL2, PDCD11 and RPS6 may serve as potential biomarkers in glioma prognosis. Importantly, GNL2 acts as an oncogene in glioma and it enhances protein synthesis to promote the development of brain glioma.

Study of prognostic splicing factors in cancer using machine learning approaches

Splicing factors (SFs) are the major RNA-binding proteins (RBPs) and key molecules that regulate the splicing of mRNA molecules through binding to mRNAs. The expression of splicing factors is frequently deregulated in different cancer types, causing the generation of oncogenic proteins involved in cancer hallmarks. In this study, we investigated the genes that encode RNA-binding proteins and identified potential splicing factors that contribute to the aberrant splicing applying a random forest classification model. The result suggested 56 splicing factors were related to the prognosis of 13 cancers, two SF complexes in liver hepatocellular carcinoma, and one SF complex in esophageal carcinoma. Further systematic bioinformatics studies on these cancer prognostic splicing factors and their related alternative splicing events revealed the potential regulations in a cancer-specific manner. Our analysis found high ILF2-ILF3 expression correlates with poor prognosis in LIHC through alternative splicing. These findings emphasize the importance of SFs as potential indicators for prognosis or targets for therapeutic interventions. Their roles in cancer exhibit complexity and are contingent upon the specific context in which they operate. This recognition further underscores the need for a comprehensive understanding and exploration of the role of SFs in different types of cancer, paving the way for their potential utilization in prognostic assessments and the development of targeted therapies.

Optimizing 5'UTRs for mRNA-delivered gene editing using deep learning

mRNA therapeutics are revolutionizing the pharmaceutical industry, but methods to optimize the primary sequence for increased expression are still lacking. Here, we design 5'UTRs for efficient mRNA translation using deep learning. We perform polysome profiling of fully or partially randomized 5'UTR libraries in three cell types and find that UTR performance is highly correlated across cell types. We train models on our datasets and use them to guide the design of high-performing 5'UTRs using gradient descent and generative neural networks. We experimentally test designed 5'UTRs with mRNA encoding megaTALTM gene editing enzymes for two different gene targets and in two different cell lines. We find that the designed 5'UTRs support strong gene editing activity. Editing efficiency is correlated between cell types and gene targets, although the best performing UTR was specific to one cargo and cell type. Our results highlight the potential of model-based sequence design for mRNA therapeutics.

RNATACs: Multispecific small molecules targeting RNA by induced proximity

RNA-targeting small molecules (rSMs) have become an attractive modality to tackle traditionally undruggable proteins and expand the druggable space. Among many innovative concepts, RNA-targeting chimeras (RNATACs) represent a new class of multispecific, induced proximity small molecules that act by chemically bringing RNA targets into proximity with an endogenous RNA effector, such as a ribonuclease (RNase). Depending on the RNA effector, RNATACs can alter the stability, localization, translation, or splicing of the target RNA. Although still in its infancy, this new modality has the potential for broad applications in the future to treat diseases with high unmet need. In this review, we discuss potential advantages of RNATACs, recent progress in the field, and challenges to this cutting-edge technology.

Comprehensive analysis of the functions, prognostic and diagnostic values of RNA binding proteins in head and neck squamous cell carcinoma

BACKGROUND

Accumulating evidence has suggested that RNA binding protein (RBP) dysregulation plays an essential role during tumorigenesis. Here, we sought to explore the potential biological functions and clinical significance of RBP and develop diagnostic and prognostic signatures based on RBP in patients with head and neck squamous cell carcinoma (HNSCC).

METHODS

The differently expressed RBPs between HNSCC samples and their normal counterparts were identified using the Limma package. The immunohistochemistry (IHC) images of several RBPs were collected from the Human Protein Atlas database. The diagnostic signature based on RBP was built by LASSO-logistic regression and random forest. The prognostic signature based on RBP was constructed by LASSO and stepwise Cox regression analysis in the training cohort and validated in the validation cohort.

RESULTS

Eighty-four aberrantly expressed RBPs were obtained, comprising 41 up-regulated and 43 down-regulated RBPs. Seven RBP genes (CPEB3, PDCD4, ENDOU, PARP12, DNMT3B, IGF2BP1, EXO1) were identified as diagnostic-related hub genes. They were used to establish a diagnostic RBP signature risk score (DRBPS) model by the coefficients in least absolute shrinkage and selection operator (LASSO)-logistic regression analysis and showed high specificity and sensitivity in the training (area under the receiver operating characteristic curve (AUC) = 0.998), and in all validation cohorts (AUC > 0.95 for all). Similarly, seven RBP genes (MKRN3, ZC3H12D, EIF5A2, AFF3, SIDT1, RBM24, and NR0B1) were identified as prognosis-associated hub genes by LASSO and stepwise multiple Cox regression analyses and were used to construct the prognostic model named as PRBPS. The AUC of the time-dependent receiver operator characteristic curve of the prognostic model was 0.664 at 3 years and 0.635 at 5 years in the training cohort and 0.720, 0.777 in the validation cohort, showing a favorable predictive efficacy for prognosis in HNSCC.

CONCLUSIONS

Our results demonstrate the value of consideration of RBP in the diagnosis and prognosis for HNSCC and provide a novel insight into understanding the potential role of dysregulated RBP in HNSCC.

Expanding the horizons of targeted protein degradation: A non-small molecule perspective

Targeted protein degradation (TPD) represented by proteolysis targeting chimeras (PROTACs) marks a significant stride in drug discovery. A plethora of innovative technologies inspired by PROTAC have not only revolutionized the landscape of TPD but have the potential to unlock functionalities beyond degradation. Non-small-molecule-based approaches play an irreplaceable role in this field. A wide variety of agents spanning a broad chemical spectrum, including peptides, nucleic acids, antibodies, and even vaccines, which not only prove instrumental in overcoming the constraints of conventional small molecule entities but also provided rapidly renewing paradigms. Herein we summarize the burgeoning non-small molecule technological platforms inspired by PROTACs, including three major trajectories, to provide insights for the design strategies based on novel paradigms.

Analysis of small EV proteomes reveals unique functional protein networks regulated by VAP-A

Extracellular vesicles (EVs) influence cell phenotypes and functions via protein, nucleic acid, and lipid cargoes. EVs are heterogeneous, due to diverse biogenesis mechanisms that remain poorly understood. Our previous study revealed that the endoplasmic reticulum (ER) membrane contact site (MCS) linker protein vesicle associated protein associated protein A (VAP-A) drives biogenesis of a subset of RNA-enriched EVs. Here, we examine the protein content of VAP-A-regulated EVs. Using label-free proteomics, we identified down- and upregulated proteins in small EVs (SEVs) purified from VAP-A knockdown (KD) colon cancer cells. Gene set enrichment analysis (GSEA) of the data revealed protein classes that are differentially sorted to SEVs dependent on VAP-A. Search Tool for the Retrieval of Reciprocity Genes (STRING) protein-protein interaction network analysis of the RNA-binding protein (RBP) gene set identified several RNA functional machineries that are downregulated in VAP-A KD SEVs, including ribosome, spliceosome, mRNA surveillance, and RNA transport proteins. We also observed downregulation of other functionally interacting protein networks, including cadherin-binding, unfolded protein binding, and ATP-dependent proteins.

CSDE1: a versatile regulator of gene expression in cancer

RNA-binding proteins (RBPs) have garnered significant attention in the field of cancer due to their ability to modulate diverse tumor traits. Once considered untargetable, RBPs have sparked renewed interest in drug development, particularly in the context of RNA-binding modulators of translation. This review focuses on one such modulator, the protein CSDE1, and its pivotal role in regulating cancer hallmarks. We discuss context-specific functions of CSDE1 in tumor development, its mechanisms of action, and highlight features that support its role as a molecular adaptor. Additionally, we discuss the regulation of CSDE1 itself and its potential value as biomarker and therapeutic target.

Deciphering the Akt1-HuD interaction in HuD-mediated neuronal differentiation

The RNA-binding protein HuD/ELAVL4 is essential for neuronal development and synaptic plasticity by governing various post-transcriptional processes of target mRNAs, including stability, translation, and localization. We previously showed that the linker region and poly(A)-binding domain of HuD play a pivotal role in promoting translation and inducing neurite outgrowth. In addition, we found that HuD interacts exclusively with the active form of Akt1, through the linker region. Although this interaction is essential for neurite outgrowth, HuD is not a substrate for Akt1, raising questions about the dynamics between HuD-mediated translational stimulation and its association with active Akt1. Here, we demonstrate that active Akt1 interacts with the cap-binding complex via HuD. We identify key amino acids in linker region of HuD responsible for Akt1 interaction, leading to the generation of two point-mutated HuD variants: one that is incapable of binding to Akt1 and another that can interact with Akt1 regardless of its phosphorylation status. In vitro translation assays using these mutants reveal that HuD-mediated translation stimulation is independent of its binding to Akt1. In addition, it is evident that the interaction between HuD and active Akt1 is essential for HuD-induced neurite outgrowth, whereas a HuD mutant capable of binding to any form of Akt1 leads to aberrant neurite development. Collectively, our results revisit the understanding of the HuD-Akt1 interaction in translation and suggest that this interaction contributes to HuD-mediated neurite outgrowth via a unique molecular mechanism distinct from translation regulation.

Tumour microenvironment programming by an RNA-RNA-binding protein complex creates a druggable vulnerability in IDH-wild-type glioblastoma

Patients with IDH-wild-type glioblastomas have a poor five-year survival rate along with limited treatment efficacy due to immune cell (glioma-associated microglia and macrophages) infiltration promoting tumour growth and resistance. To enhance therapeutic options, our study investigated the unique RNA-RNA-binding protein complex LOC-DHX15. This complex plays a crucial role in driving immune cell infiltration and tumour growth by establishing a feedback loop between cancer and immune cells, intensifying cancer aggressiveness. Targeting this complex with blood-brain barrier-permeable small molecules improved treatment efficacy, disrupting cell communication and impeding cancer cell survival and stem-like properties. Focusing on RNA-RNA-binding protein interactions emerges as a promising approach not only for glioblastomas without the IDH mutation but also for potential applications beyond cancer, offering new avenues for developing therapies that address intricate cellular relationships in the body.

ePRINT: exonuclease assisted mapping of protein-RNA interactions

RNA-binding proteins (RBPs) regulate key aspects of RNA processing including alternative splicing, mRNA degradation and localization by physically binding RNA molecules. Current methods to map these interactions, such as CLIP, rely on purifying single proteins at a time. Our new method, ePRINT, maps RBP-RNA interaction networks on a global scale without purifying individual RBPs. ePRINT uses exoribonuclease XRN1 to precisely map the 5' end of the RBP binding site and uncovers direct and indirect targets of an RBP of interest. Importantly, ePRINT can also uncover RBPs that are differentially activated between cell fate transitions, including neural progenitor differentiation into neurons.

Imaging the dynamics of messenger RNA with a bright and stable green fluorescent RNA

Fluorescent RNAs (FRs) provide an attractive approach to visualizing RNAs in live cells. Although the color palette of FRs has been greatly expanded recently, a green FR with high cellular brightness and photostability is still highly desired. Here we develop a fluorogenic RNA aptamer, termed Okra, that can bind and activate the fluorophore ligand ACE to emit bright green fluorescence. Okra has an order of magnitude enhanced cellular brightness than currently available green FRs, allowing the robust imaging of messenger RNA in both live bacterial and mammalian cells. We further demonstrate the usefulness of Okra for time-resolved measurements of ACTB mRNA trafficking to stress granules, as well as live-cell dual-color superresolution imaging of RNA in combination with Pepper620, revealing nonuniform and distinct distributions of different RNAs throughout the granules. The favorable properties of Okra make it a versatile tool for the study of RNA dynamics and subcellular localization.

Dynamics of Protein-RNA Interfaces Using All-Atom Molecular Dynamics Simulations

Facing the current challenges posed by human health diseases requires the understanding of cell machinery at a molecular level. The interplay between proteins and RNA is key for any physiological phenomenon, as well protein-RNA interactions. To understand these interactions, many experimental techniques have been developed, spanning a very wide range of spatial and temporal resolutions. In particular, the knowledge of tridimensional structures of protein-RNA complexes provides structural, mechanical, and dynamical pieces of information essential to understand their functions. To get insights into the dynamics of protein-RNA complexes, we carried out all-atom molecular dynamics simulations in explicit solvent on nine different protein-RNA complexes with different functions and interface size by taking into account the bound and unbound forms. First, we characterized structural changes upon binding and, for the RNA part, the change in the puckering. Second, we extensively analyzed the interfaces, their dynamics and structural properties, and the structural waters involved in the binding, as well as the contacts mediated by them. Based on our analysis, the interfaces rearranged during the simulation time showing alternative and stable residue-residue contacts with respect to the experimental structure.

Genome-wide identification and analysis of epithelial-mesenchymal transition-related RNA-binding proteins and alternative splicing in a human breast cancer cell line

Exploring the mechanism of breast cancer metastasis and searching for new drug therapeutic targets are still the focuses of current research. RNA-binding proteins (RBPs) may affect breast cancer metastasis by regulating alternative splicing (AS) during epithelial-mesenchymal transition (EMT). We hypothesised that during EMT development in breast cancer cells, the expression level of RBPs and the gene AS pattern in the cell were significantly changed on a genome-wide scale. Using GEO database, this study identified differentially expressed RBPs and differential AS events at different stages of EMT in breast cancer cells. By establishing the correlation network of differential RBPs and differential AS events, we found that RBM47, PCBP3, FRG1, SRP72, RBMS3 and other RBPs may regulate the AS of ITGA6, ADGRE5, TNC, COL6A3 and other cell adhesion genes. By further analysing above EMT-related RBPs and AS in breast cancer tissues in TCGA, it was found that the expression levels of ADAT2, C2orf15, SRP72, PAICS, RBMS3, APOBEC3G, NOA1, ACO1 and the AS of TNC and COL6A3 were significantly correlated with the prognosis of breast cancer patients. The expression levels of all 8 RBPs were significantly different in breast cancer tissues without metastasis compared with normal breast tissues. Conclusively, eight RBPs such as RBMS3 and AS of TNC and COL6A3 could be used as predictors of breast cancer prognosis. These findings need to be further explored as possible targets for breast cancer treatment.

Improved prediction of DNA and RNA binding proteins with deep learning models

Nucleic acid-binding proteins (NABPs), including DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs), play important roles in essential biological processes. To facilitate functional annotation and accurate prediction of different types of NABPs, many machine learning-based computational approaches have been developed. However, the datasets used for training and testing as well as the prediction scopes in these studies have limited their applications. In this paper, we developed new strategies to overcome these limitations by generating more accurate and robust datasets and developing deep learning-based methods including both hierarchical and multi-class approaches to predict the types of NABPs for any given protein. The deep learning models employ two layers of convolutional neural network and one layer of long short-term memory. Our approaches outperform existing DBP and RBP predictors with a balanced prediction between DBPs and RBPs, and are more practically useful in identifying novel NABPs. The multi-class approach greatly improves the prediction accuracy of DBPs and RBPs, especially for the DBPs with ~12% improvement. Moreover, we explored the prediction accuracy of single-stranded DNA binding proteins and their effect on the overall prediction accuracy of NABP predictions.

Broad proteomics analysis of seeding-induced aggregation of α-synuclein in M83 neurons reveals remodeling of proteostasis mechanisms that might contribute to Parkinson's disease pathogenesis

Aggregation of misfolded α-synuclein (α-syn) is a key characteristic feature of Parkinson's disease (PD) and related synucleinopathies. The nature of these aggregates and their contribution to cellular dysfunction is still not clearly elucidated. We employed mass spectrometry-based total and phospho-proteomics to characterize the underlying molecular and biological changes due to α-syn aggregation using the M83 mouse primary neuronal model of PD. We identified gross changes in the proteome that coincided with the formation of large Lewy body-like α-syn aggregates in these neurons. We used protein-protein interaction (PPI)-based network analysis to identify key protein clusters modulating specific biological pathways that may be dysregulated and identified several mechanisms that regulate protein homeostasis (proteostasis). The observed changes in the proteome may include both homeostatic compensation and dysregulation due to α-syn aggregation and a greater understanding of both processes and their role in α-syn-related proteostasis may lead to improved therapeutic options for patients with PD and related disorders.

Live cell screening to identify RNA-binding small molecule inhibitors of the pre-let-7-Lin28 RNA-protein interaction

Dysregulation of the networking of RNA-binding proteins (RBPs) and RNAs drives many human diseases, including cancers, and the targeting of RNA-protein interactions (RPIs) has emerged as an exciting area of RNA-targeted drug discovery. Accordingly, methods that enable the discovery of cell-active small molecule modulators of RPIs are needed to propel this emerging field forward. Herein, we describe the application of live-cell assay technology, RNA interaction with protein-mediated complementation assay (RiPCA), for high-throughput screening to identify small molecule inhibitors of the pre-let-7d-Lin28A RPI. Utilizing a combination of RNA-biased small molecules and virtual screening hits, we discovered an RNA-binding small molecule that can disrupt the pre-let-7-Lin28 interaction demonstrating the potential of RiPCA for advancing RPI-targeted drug discovery.

Integrative multi-omic analysis reveals conserved cell-projection deficits in human Down syndrome brains

Down syndrome (DS) is the most common genetic cause of cognitive disability. However, it is largely unclear how triplication of a small gene subset may impinge on diverse aspects of DS brain physiopathology. Here, we took a multi-omic approach and simultaneously analyzed by RNA-seq and proteomics the expression signatures of two diverse regions of human postmortem DS brains. We found that the overexpression of triplicated genes triggered global expression dysregulation, differentially affecting transcripts, miRNAs, and proteins involved in both known and novel biological candidate pathways. Among the latter, we observed an alteration in RNA splicing, specifically modulating the expression of genes involved in cytoskeleton and axonal dynamics in DS brains. Accordingly, we found an alteration in axonal polarization in neurons from DS human iPSCs and mice. Thus, our study provides an integrated multilayer expression database capable of identifying new potential targets to aid in designing future clinical interventions for DS.

IGF2BP3 promotes glutamine metabolism of endometriosis by interacting with UCA1 to enhances the mRNA stability of GLS1

BACKGROUND

Insulin like growth factor II mRNA binding protein 3 (IGF2BP3) has been implicated in numerous inflammatory and cancerous conditions. However, its precise molecular mechanisms in endometriosis (EMs) remains unclear. The aim of this study is to examine the influence of IGF2BP3 on the occurrence and progression of EMs and to elucidate its underlying molecular mechanism.

METHODS

Efects of IGF2BP3 on endometriosis were confrmed in vitro and in vivo. Based on bioinformatics analysis, RNA immunoprecipitation (RIP), RNA pull-down assays and Fluorescent in situ hybridization (FISH) were used to show the association between IGF2BP3 and UCA1. Single-cell spatial transcriptomics analysis shows the expression distribution of glutaminase 1 (GLS1) mRNA in EMs. Study the effect on glutamine metabolism after ectopic endometriotic stromal cells (eESCs) were transfected with Sh-IGF2BP3 and Sh-UCA1 lentivirus.

RESULTS

Immunohistochemical staining have revealed that IGF2BP3 was upregulated in ectopic endometriotic lesions (EC) compared to normal endometrial tissues (EN). The proliferation and migration ability of eESCs were greatly reduced by downregulating IGF2BP3. Additionally, IGF2BP3 has been observed to interact with urothelial carcinoma associated 1 (UCA1), leading to increased stability of GLS1 mRNA and subsequently enhancing glutamine metabolism. Results also demonstrated that IGF2BP3 directly interacts with the 3' UTR region of GLS1 mRNA, influencing its expression and stability. Furthermore, UCA1 was able to bind with c-MYC protein, stabilizing c-MYC mRNA and consequently enhancing GLS1 expression through transcriptional promotion.

CONCLUSION

These discoveries underscored the critical involvement of IGF2BP3 in the elevation and stability of GLS1 mRNA in the context of glutamine metabolism by interacting with UCA1 in EMs. The implications of our study extended to the identification of possible therapeutic targets for individuals with EMs.

Proteomic Profiles Associated With Postsurgical Progression in Nonfunctioning Pituitary Adenomas

CONTEXT

There is a lack of reliable biomarkers capable of predicting postoperative tumor progression of nonfunctioning pituitary adenomas (NFPAs).

OBJECTIVE

To discover proteomic profiles associated with postoperative tumor progression in patients with NFPAs. This was a case-controlled exploratory study at a tertiary university hospital. Tissue samples were obtained from 46 patients with residual tumor following surgery for NFPAs of gonadotroph lineage. Two patient groups were compared: patients requiring reintervention due to residual tumor progression (cases; reintervention group, n = 29) and patients with a residual tumor showing no progression for a minimum of 5 years (controls; radiologically stable group, n = 17). Differentially expressed proteins (DEPs) between patient groups were measured.

RESULTS

Global quantitative proteomic analysis identified 4074 proteins, of which 550 were differentially expressed between the 2 groups (fold change >80%, false discovery rate-adjusted P ≤ .05). Principal component analysis showed good separation between the 2 groups. Functional enrichment analysis of the DEPs indicated processes involving translation, ROBO-receptor signaling, energy metabolism, mRNA metabolism, and RNA splicing. Several upregulated proteins in the reintervention group, including SNRPD1, SRSF10, SWAP-70, and PSMB1, are associated with tumor progression in other cancer types.

CONCLUSION

This is the first exploratory study analyzing proteomic profiles as markers of postoperative tumor progression in NFPAs. The findings clearly showed different profiles between tumors with indolent postoperative behavior and those with postoperative tumor progression. Both enriched pathways involving DEPs and specific upregulated proteins have previously been associated with tumor aggressiveness. These results suggest the value of proteomic profiling for predicting tumor progression in patients with NFPAs.

The binding of LARP6 and DNAAF6 in biomolecular condensates influences ciliogenesis of multiciliated cells

Motile cilia on the cell surface produce fluid flows in the body and abnormalities in motile cilia cause primary ciliary dyskinesia. Dynein axonemal assembly factor 6 (DNAAF6), a causative gene of primary ciliary dyskinesia, was isolated as an interacting protein with La ribonucleoprotein 6 (LARP6) that regulates ciliogenesis in multiciliated cells (MCCs). In MCCs of Xenopus embryos, LARP6 and DNAAF6 were colocalized in biomolecular condensates termed dynein axonemal particles and synergized to control ciliogenesis. Moreover, tubulin alpha 1c-like mRNA encoding α-tubulin protein, that is a major component of ciliary axoneme, was identified as a target mRNA regulated by binding LARP6. While DNAAF6 was necessary for high α-tubulin protein expression near the apical side of Xenopus MCCs during ciliogenesis, its mutant, which abolishes binding with LARP6, was unable to restore the expression of α-tubulin protein near the apical side of MCCs in Xenopus DNAAF6 morphant. These results indicated that the binding of LARP6 and DNAAF6 in dynein axonemal particles regulates highly expressed α-tubulin protein near the apical side of Xenopus MCCs during ciliogenesis.

RNA binding proteins as mediators of pathological cardiac remodeling

RNA binding proteins (RBPs) play a central in the post-transcriptional regulation of gene expression, which can account for up to 50% of all variations in protein expression within a cell. Following their binding to target RNAs, RBPs most typically confer changes in gene expression through modulation of alternative spicing, RNA stabilization/degradation, or ribosome loading/translation rate. All of these post-transcriptional regulatory processes have been shown to play a functional role in pathological cardiac remodeling, and a growing body of evidence is beginning to identify the mechanistic contribution of individual RBPs and their cardiac RNA targets. This review highlights the mechanisms of RBP-dependent post-transcriptional gene regulation in cardiomyocytes and fibroblasts and our current understanding of how RNA binding proteins functionally contribute to pathological cardiac remodeling.

Deep Learning for Elucidating Modifications to RNA-Status and Challenges Ahead

RNA-binding proteins and chemical modifications to RNA play vital roles in the co- and post-transcriptional regulation of genes. In order to fully decipher their biological roles, it is an essential task to catalogue their precise target locations along with their preferred contexts and sequence-based determinants. Recently, deep learning approaches have significantly advanced in this field. These methods can predict the presence or absence of modification at specific genomic regions based on diverse features, particularly sequence and secondary structure, allowing us to decipher the highly non-linear sequence patterns and structures that underlie site preferences. This article provides an overview of how deep learning is being applied to this area, with a particular focus on the problem of mRNA-RBP binding, while also considering other types of chemical modification to RNA. It discusses how different types of model can handle sequence-based and/or secondary-structure-based inputs, the process of model training, including choice of negative regions and separating sets for testing and training, and offers recommendations for developing biologically relevant models. Finally, it highlights four key areas that are crucial for advancing the field.

MAPP unravels frequent co-regulation of splicing and polyadenylation by RNA-binding proteins and their dysregulation in cancer

Maturation of eukaryotic pre-mRNAs via splicing and polyadenylation is modulated across cell types and conditions by a variety of RNA-binding proteins (RBPs). Although there exist over 1,500 RBPs in human cells, their binding motifs and functions still remain to be elucidated, especially in the complex environment of tissues and in the context of diseases. To overcome the lack of methods for the systematic and automated detection of sequence motif-guided pre-mRNA processing regulation from RNA sequencing (RNA-Seq) data we have developed MAPP (Motif Activity on Pre-mRNA Processing). Applying MAPP to RBP knock-down experiments reveals that many RBPs regulate both splicing and polyadenylation of nascent transcripts by acting on similar sequence motifs. MAPP not only infers these sequence motifs, but also unravels the position-dependent impact of the RBPs on pre-mRNA processing. Interestingly, all investigated RBPs that act on both splicing and 3' end processing exhibit a consistently repressive or activating effect on both processes, providing a first glimpse on the underlying mechanism. Applying MAPP to normal and malignant brain tissue samples unveils that the motifs bound by the PTBP1 and RBFOX RBPs coordinately drive the oncogenic splicing program active in glioblastomas demonstrating that MAPP paves the way for characterizing pre-mRNA processing regulators under physiological and pathological conditions.

RNP granules in ALS and neurodegeneration: From multifunctional membraneless organelles to therapeutic opportunities

Amyotrophic lateral sclerosis (ALS) and related neurodegenerative diseases are characterised by dysfunction of a host of RNA-binding proteins (RBPs) and a severely disrupted RNA metabolism. Recently, RBP-harbouring phase-separated complexes, ribonucleoprotein (RNP) granules, have come into the limelight as "crucibles" of neuronal pathology in ALS. RNP granules are indispensable for the multitude of regulatory processes underlying cellular RNA metabolism and serve as critical organisers of cellular biochemistry. Neurons, highly specialised cells, heavily rely on RNP granules for efficient trafficking, signalling and stress responses. Multiple RNP granule components, primarily RBPs such as TDP-43 and FUS, are affected by ALS mutations. However, even in the absence of mutations, RBP proteinopathies represent pathophysiological hallmarks of ALS. Given the high local concentrations of RBPs and RNAs, their weakened or enhanced interactions within RNP granules disrupt their homeostasis. Thus, the physiological process of phase separation and RNP granule formation, vital for maintaining the high-functioning state of neuronal cells, becomes their Achilles heel. Here, we will review the recent literature on the causes and consequences of abnormal RNP granule functioning in ALS and related disorders. In particular, we will summarise the evidence for the network-level dysfunction of RNP granules in these conditions and discuss considerations for therapeutic interventions to target RBPs, RNP granules and their network as a whole.

SAFB regulates hippocampal stem cell fate by targeting Drosha to destabilize Nfib mRNA

Neural stem cells (NSCs) are multipotent and correct fate determination is crucial to guarantee brain formation and homeostasis. How NSCs are instructed to generate neuronal or glial progeny is not well understood. Here, we addressed how murine adult hippocampal NSC fate is regulated and described how scaffold attachment factor B (SAFB) blocks oligodendrocyte production to enable neuron generation. We found that SAFB prevents NSC expression of the transcription factor nuclear factor I/B (NFIB) by binding to sequences in the Nfib mRNA and enhancing Drosha-dependent cleavage of the transcripts. We show that increasing SAFB expression prevents oligodendrocyte production by multipotent adult NSCs, and conditional deletion of Safb increases NFIB expression and oligodendrocyte formation in the adult hippocampus. Our results provide novel insights into a mechanism that controls Drosha functions for selective regulation of NSC fate by modulating the post-transcriptional destabilization of Nfib mRNA in a lineage-specific manner.

PRMT5-mediated arginine methylation of FXR1 is essential for RNA binding in cancer cells

Emerging evidence indicates that arginine methylation promotes the stability of arginine-glycine-rich (RGG) motif-containing RNA-binding proteins (RBPs) and regulates gene expression. Here, we report that post-translational modification of FXR1 enhances the binding with mRNAs and is involved in cancer cell growth and proliferation. Independent point mutations in arginine residues of FXR1's nuclear export signal (R386 and R388) and RGG (R453, R455 and R459) domains prevent it from binding to RNAs that form G-quadruplex (G4) RNA structures. Disruption of G4-RNA structures by lithium chloride failed to bind with FXR1, indicating its preference for G4-RNA structure containing mRNAs. Furthermore, loss-of-function of PRMT5 inhibited FXR1 methylation both in vivo and in vitro, affecting FXR1 protein stability, inhibiting RNA-binding activity and cancer cell growth and proliferation. Finally, the enhanced crosslinking and immunoprecipitation (eCLIP) analyses reveal that FXR1 binds with the G4-enriched mRNA targets such as AHNAK, MAP1B, AHNAK2, HUWE1, DYNC1H1 and UBR4 and controls its mRNA expression in cancer cells. Our findings suggest that PRMT5-mediated FXR1 methylation is required for RNA/G4-RNA binding, which promotes gene expression in cancer cells. Thus, FXR1's structural characteristics and affinity for RNAs preferentially G4 regions provide new insights into the molecular mechanism of FXR1 in oral cancer cells.

Single-cell transcriptome revealed dysregulated RNA-binding protein expression patterns and functions in human ankylosing spondylitis

Objective

To explore the expression characteristics and regulatory patterns of RBPs in different immune cell types of AS, and to clarify the potential key role of RBPs in the occurrence and development of AS disease.

Methods

PBMC sample data from scRNA-seq (HC*29, AS*10) and bulk RNA-seq (NC*3, AS*5) were selected for correlation analysis.

Results

(1) Compared with the HC group, the numbers of B, DC (dendritic cells), CD14+ Mono and CD8+ T cells were increased in AS group, while the numbers of platelet (platelets), CD8+ NKT, CD16+ Mono (non-classical monocytes), Native CD4+ T and NK were decreased. (2) Through the analysis of RBP genes in B cells, some RBPs were found to play an important role in B cell differentiation and function, such as DDX3X, SFPQ, SRRM1, UPF2. (3) It may be related to B-cell receptor, IgA immunity, NOD-like receptor and other signaling pathways; Through the analysis of RBP genes in CD8+ T cells, some RBPs that play an important role in the immune regulation of CD8+ T were found, such as EIF2S3, EIF4B, HSPA5, MSL3, PABPC1 and SRSF7; It may be related to T cell receptor, TNF, IL17 and other signaling pathways. (4) Based on bulk RNA-seq, it was found that compared with HC and AS patients, differentially expressed variable splicing genes (RASGs) may play an important role in the occurrence and development of AS by participating in transcriptional regulation, protein phosphorylation and ubiquitination, DNA replication, angiogenesis, intracellular signal transduction and other related pathways.

Conclusion

RBPs has specific expression characteristics in different immune cell types of AS patients, and has important regulatory functions. Its abnormal expression and regulation may be closely related to the occurrence and development of AS.

Time-resolved profiling of RNA binding proteins throughout the mRNA life cycle

mRNAs continually change their protein partners throughout their lifetimes, yet our understanding of mRNA-protein complex (mRNP) remodeling is limited by a lack of temporal data. Here, we present time-resolved mRNA interactome data by performing pulse metabolic labeling with photoactivatable ribonucleoside in human cells, UVA crosslinking, poly(A)+ RNA isolation, and mass spectrometry. This longitudinal approach allowed the quantification of over 700 RNA binding proteins (RBPs) across ten time points. Overall, the sequential order of mRNA binding aligns well with known functions, subcellular locations, and molecular interactions. However, we also observed RBPs with unexpected dynamics: the transcription-export (TREX) complex recruited posttranscriptionally after nuclear export factor 1 (NXF1) binding, challenging the current view of transcription-coupled mRNA export, and stress granule proteins prevalent in aged mRNPs, indicating roles in late stages of the mRNA life cycle. To systematically identify mRBPs with unknown functions, we employed machine learning to compare mRNA binding dynamics with Gene Ontology (GO) annotations. Our data can be explored at chronology.rna.snu.ac.kr.

Deciphering novel TCF4-driven mechanisms underlying a common triplet repeat expansion-mediated disease

Fuchs endothelial corneal dystrophy (FECD) is an age-related cause of vision loss, and the most common repeat expansion-mediated disease in humans characterised to date. Up to 80% of European FECD cases have been attributed to expansion of a non-coding CTG repeat element (termed CTG18.1) located within the ubiquitously expressed transcription factor encoding gene, TCF4. The non-coding nature of the repeat and the transcriptomic complexity of TCF4 have made it extremely challenging to experimentally decipher the molecular mechanisms underlying this disease. Here we comprehensively describe CTG18.1 expansion-driven molecular components of disease within primary patient-derived corneal endothelial cells (CECs), generated from a large cohort of individuals with CTG18.1-expanded (Exp+) and CTG 18.1-independent (Exp-) FECD. We employ long-read, short-read, and spatial transcriptomic techniques to interrogate expansion-specific transcriptomic biomarkers. Interrogation of long-read sequencing and alternative splicing analysis of short-read transcriptomic data together reveals the global extent of altered splicing occurring within Exp+ FECD, and unique transcripts associated with CTG18.1-expansions. Similarly, differential gene expression analysis highlights the total transcriptomic consequences of Exp+ FECD within CECs. Furthermore, differential exon usage, pathway enrichment and spatial transcriptomics reveal TCF4 isoform ratio skewing solely in Exp+ FECD with potential downstream functional consequences. Lastly, exome data from 134 Exp- FECD cases identified rare (minor allele frequency <0.005) and potentially deleterious (CADD>15) TCF4 variants in 7/134 FECD Exp- cases, suggesting that TCF4 variants independent of CTG18.1 may increase FECD risk. In summary, our study supports the hypothesis that at least two distinct pathogenic mechanisms, RNA toxicity and TCF4 isoform-specific dysregulation, both underpin the pathophysiology of FECD. We anticipate these data will inform and guide the development of translational interventions for this common triplet-repeat mediated disease.

Adipocyte-Specific Hnrnpa1 Knockout Aggravates Obesity-Induced Metabolic Dysfunction via Upregulation of CCL2

Heterogeneous nuclear ribonucleoprotein A1 (HNRNPA1) is involved in lipid and glucose metabolism via mRNA processing. However, whether and how HNRNPA1 alters adipocyte function in obesity remain obscure. Here, we found that the obese state downregulated HNRNPA1 expression in white adipose tissue (WAT). The depletion of adipocyte HNRNPA1 promoted markedly increased macrophage infiltration and expression of proinflammatory and fibrosis genes in WAT of obese mice, eventually leading to exacerbated insulin sensitivity, glucose tolerance, and hepatic steatosis. Mechanistically, HNRNPA1 interacted with Ccl2 and regulated its mRNA stability. Intraperitoneal injection of CCL2-CCR2 signaling antagonist improved adipose tissue inflammation and systemic glucose homeostasis. Furthermore, HNRNPA1 expression in human WAT was negatively correlated with BMI, fat percentage, and subcutaneous fat area. Among individuals with 1-year metabolic surgery follow-up, HNRNPA1 expression was positively related to percentage of total weight loss. These findings identify adipocyte HNRNPA1 as a link between adipose tissue inflammation and systemic metabolic homeostasis, which might be a promising therapeutic target for obesity-related disorders.

ARTICLE HIGHLIGHTS

Identification and classification of glioma subtypes based on RNA-binding proteins

BACKGROUND

Glioma is a common and aggressive primary malignant cancer known for its high morbidity, mortality, and recurrence rates. Despite this, treatment options for glioma are currently restricted. The dysregulation of RBPs has been linked to the advancement of several types of cancer, but their precise role in glioma evolution is still not fully understood. This study sought to investigate how RBPs may impact the development and prognosis of glioma, with potential implications for prognosis and therapy.

METHODS

RNA-seq profiles of glioma and corresponding clinical data from the CGGA database were initially collected for analysis. Unsupervised clustering was utilized to identify crucial tumor subtypes in glioma development. Subsequent time-series analysis and MS model were employed to track the progression of these identified subtypes. RBPs playing a significant role in glioma progression were then pinpointed using WGCNA and Lasso Cox regression models. Functional analysis of these key RBP-related genes was conducted through GSEA. Additionally, the CIBERSORT algorithm was utilized to estimate immune infiltrating cells, while the STRING database was consulted to uncover potential mechanisms of the identified biomarkers.

RESULTS

Six tumor subgroups were identified and found to be highly homogeneous within each subgroup. The progression stages of these tumor subgroups were determined using time-series analysis and a MS model. Through WGCNA, Lasso Cox, and multivariate Cox regression analysis, it was confirmed that BCLAF1 is correlated with survival in glioma patients and is closely linked to glioma progression. Functional annotation suggests that BCLAF1 may impact glioma progression by influencing RNA splicing, which in turn affects the cell cycle, Wnt signaling pathway, and other cancer development pathways.

CONCLUSIONS

The study initially identified six subtypes of glioma progression and assessed their malignancy ranking. Furthermore, it was determined that BCLAF1 could serve as an RBP-related prognostic marker, offering significant implications for the clinical diagnosis and personalized treatment of glioma.

Ewing Sarcoma Related protein 1 recognizes R-loops by binding DNA forks

EWSR1 (Ewing Sarcoma Related protein 1) is an RNA binding protein that is ubiquitously expressed across cell lines and involved in multiple parts of RNA processing, such as transcription, splicing, and mRNA transport. EWSR1 has also been implicated in cellular mechanisms to control formation of R-loops, a three-stranded nucleic acid structure consisting of a DNA:RNA hybrid and a displaced single-stranded DNA strand. Unscheduled R-loops result in genomic and transcription stress. Loss of function of EWSR1 functions commonly found in Ewing Sarcoma correlates with high abundance of R-loops. In this study, we investigated the mechanism for EWSR1 to recognize an R-loop structure specifically. Using electrophoretic mobility shift assays (EMSA), we detected the high affinity binding of EWSR1 to substrates representing components found in R-loops. EWSR1 specificity could be isolated to the DNA fork region, which transitions between double- and single-stranded DNA. Our data suggests that the Zinc-finger domain (ZnF) with flanking arginine and glycine rich (RGG) domains provide high affinity binding, while the RNA recognition motif (RRM) with its RGG domains offer improved specificity. This model offers a rational for EWSR1 specificity to encompass a wide range in contexts due to the DNA forks always found with R-loops.

eCRUIS captures RNA-protein interaction in vitro and in vivo

As an information bridge between DNA and protein, RNA regulates cellular processes and gene expression in various ways. From its synthesis to degradation, RNA is associated with a range of RNA-binding proteins. Therefore, it is necessary to develop innovative methods to study the interaction between RNA and proteins. Previously, we developed an RNA-centric method, called CRISPR-based RNA-United Interacting System (CRUIS), to capture RNA-protein interaction in cells. On this basis, here we develop an enhanced CRUIS (eCRUIS) by combining the power of dCas13d and the engineered promiscuous ligase TurboID. The current version allows us to rapidly label RNA-binding proteins on the target RNA within 30 minutes, potentially for in vivo use. By introducing bait-assay with exogenous RNA, we confirm that eCRUIS can effectively label RNA-binding proteins on bait RNA in a short time. eCRUIS provides a broader range of in vitro and in vivo applications for studying RNA-protein interactions.

Role of mRNA-binding proteins in retinal neovascularization

Retinal neovascularization (RNV) is a pathological process that primarily occurs in diabetic retinopathy, retinopathy of prematurity, and retinal vein occlusion. It is a common yet debilitating clinical condition that culminates in blindness. Urgent efforts are required to explore more efficient and less limiting therapeutic strategies. Key RNA-binding proteins (RBPs), crucial for post-transcriptional regulation of gene expression by binding to RNAs, are closely correlated with RNV development. RBP-RNA interactions are altered during RNV. Here, we briefly review the characteristics and functions of RBPs, and the mechanism of RNV. Then, we present insights into the role of the regulatory network of RBPs in RNV. HuR, eIF4E, LIN28B, SRSF1, METTL3, YTHDF1, Gal-1, HIWI1, and ZFR accelerate RNV progression, whereas YTHDF2 and hnRNPA2B1 hinder it. The mechanisms elucidated in this review provide a reference to guide the design of therapeutic strategies to reverse abnormal processes.

NR1D1-transactivated lncRNA NUTM2A-AS1 promotes chemoresistance and immune evasion in neuroblastoma via inhibiting B7-H3 degradation

Neuroblastoma (NB), a common solid tumour in young children originating from the sympathetic nervous system during embryonic development, poses challenges despite therapeutic advances like high-dose chemotherapy and immunotherapy. Some survivors still grapple with severe side effects and drug resistance. The role of lncRNA NUTM2A-AS1 has been explored in various cancers, but its function in drug-resistant NB progression is unclear. Our study found that NUTM2A-AS1 expression in cisplatin-resistant NB cells increased in a time- and dose-dependent manner. Knockdown of NUTM2A-AS1 significantly improved NB cell sensitivity to cisplatin and inhibited metastatic abilities. Additionally, we identified B7-H3, an immune checkpoint-related protein, as a NUTM2A-AS1-associated protein in NB cells. NUTM2A-AS1 was shown to inhibit the protein degradation of B7-H3. Moreover, NUTM2A-AS1 modulated immune evasion in cisplatin-resistant NB cells through B7-H3. Furthermore, NUTM2A-AS1 expression in cisplatin-resistant NB cells was transactivated by NR1D1. In summary, our results unveil the molecular or biological relationship within the NR1D1/NUTM2A-AS1/B7-H3 axis in NB cells under cisplatin treatment, providing an intriguing avenue for fundamental research into cisplatin-resistant NB.

Cold-shock proteome of myoblasts reveals role of RBM3 in promotion of mitochondrial metabolism and myoblast differentiation

Adaptation to hypothermia is important for skeletal muscle cells under physiological stress and is used for therapeutic hypothermia (mild hypothermia at 32  °C). We show that hypothermic preconditioning at 32  °C for 72 hours improves the differentiation of skeletal muscle myoblasts using both C2C12 and primary myoblasts isolated from 3 month and 18-month-old mice. We analyzed the cold-shock proteome of myoblasts exposed to hypothermia (32  °C for 6 and 48 h) and identified significant changes in pathways related to RNA processing and central carbon, fatty acid, and redox metabolism. The analysis revealed that levels of the cold-shock protein RBM3, an RNA-binding protein, increases with both acute and chronic exposure to hypothermic stress, and is necessary for the enhanced differentiation and maintenance of mitochondrial metabolism. We also show that overexpression of RBM3 at 37  °C is sufficient to promote mitochondrial metabolism, cellular proliferation, and differentiation of C2C12 and primary myoblasts. Proteomic analysis of C2C12 myoblasts overexpressing RBM3 show significant enrichment of pathways involved in fatty acid metabolism, RNA metabolism and the electron transport chain. Overall, we show that the cold-shock protein RBM3 is a critical factor that can be used for controlling the metabolic network of myoblasts.

UPF1 regulates mRNA stability by sensing poorly translated coding sequences

Post-transcriptional mRNA regulation shapes gene expression, yet how cis-elements and mRNA translation interface to regulate mRNA stability is poorly understood. We find that the strength of translation initiation, upstream open reading frame (uORF) content, codon optimality, AU-rich elements, microRNA binding sites, and open reading frame (ORF) length function combinatorially to regulate mRNA stability. Machine-learning analysis identifies ORF length as the most important conserved feature regulating mRNA decay. We find that Upf1 binds poorly translated and untranslated ORFs, which are associated with a higher decay rate, including mRNAs with uORFs and those with exposed ORFs after stop codons. Our study emphasizes Upf1's converging role in surveilling mRNAs with exposed ORFs that are poorly translated, such as mRNAs with long ORFs, ORF-like 3' UTRs, and mRNAs containing uORFs. We propose that Upf1 regulation of poorly/untranslated ORFs provides a unifying mechanism of surveillance in regulating mRNA stability and homeostasis in an exon-junction complex (EJC)-independent nonsense-mediated decay (NMD) pathway that we term ORF-mediated decay (OMD).

DDX20 is required for cell-cycle reentry of prospermatogonia and establishment of spermatogonial stem cell pool during testicular development in mice

RNA-binding proteins (RBPs), as key regulators of mRNA fate, are abundantly expressed in the testis. However, RBPs associated with human male infertility remain largely unknown. Through bioinformatic analyses, we identified 62 such RBPs, including an evolutionarily conserved RBP, DEAD-box helicase 20 (DDX20). Male germ-cell-specific inactivation of Ddx20 at E15.5 caused T1-propsermatogonia (T1-ProSG) to fail to reenter cell cycle during the first week of testicular development in mice. Consequently, neither the foundational spermatogonial stem cell (SSC) pool nor progenitor spermatogonia were ever formed in the knockout testes. Mechanistically, DDX20 functions to control the translation of its target mRNAs, many of which encode cell-cycle-related regulators, by interacting with key components of the translational machinery in prospermatogonia. Our data demonstrate a previously unreported function of DDX20 as a translational regulator of critical cell-cycle-related genes, which is essential for cell-cycle reentry of T1-ProSG and formation of the SSC pool.

Protein click chemistry and its potential for medical applications

A revolution in chemical biology occurred with the introduction of click chemistry. Click chemistry plays an important role in protein chemistry modifications, providing specific, sensitive, rapid, and easy-to-handle methods. Under physiological conditions, click chemistry often overlaps with bioorthogonal chemistry, defined as reactions that occur rapidly and selectively without interfering with biological processes. Click chemistry is used for the posttranslational modification of proteins based on covalent bond formations. With the contribution of click reactions, selective modification of proteins would be developed, representing an alternative to other technologies in preparing new proteins or enzymes for studying specific protein functions in different biological processes. Click-modified proteins have potential in diverse applications such as imaging, labeling, sensing, drug design, and enzyme technology. Due to the promising role of proteins in disease diagnosis and therapy, this review aims to highlight the growing applications of click strategies in protein chemistry over the last two decades, with a special emphasis on medicinal applications.

Hammerhead-type FXR agonists induce an enhancer RNA Fincor that ameliorates nonalcoholic steatohepatitis in mice

The nuclear receptor, farnesoid X receptor (FXR/NR1H4), is increasingly recognized as a promising drug target for metabolic diseases, including nonalcoholic steatohepatitis (NASH). Protein-coding genes regulated by FXR are well known, but whether FXR also acts through regulation of long non-coding RNAs (lncRNAs), which vastly outnumber protein-coding genes, remains unknown. Utilizing RNA-seq and global run-on sequencing (GRO-seq) analyses in mouse liver, we found that FXR activation affects the expression of many RNA transcripts from chromatin regions bearing enhancer features. Among these we discovered a previously unannotated liver-enriched enhancer-derived lncRNA (eRNA), termed FXR-induced non-coding RNA (Fincor). We show that Fincor is specifically induced by the hammerhead-type FXR agonists, including GW4064 and tropifexor. CRISPR/Cas9-mediated liver-specific knockdown of Fincor in dietary NASH mice reduced the beneficial effects of tropifexor, an FXR agonist currently in clinical trials for NASH and primary biliary cholangitis (PBC), indicating that amelioration of liver fibrosis and inflammation in NASH treatment by tropifexor is mediated in part by Fincor. Overall, our findings highlight that pharmacological activation of FXR by hammerhead-type agonists induces a novel eRNA, Fincor, contributing to the amelioration of NASH in mice. Fincor may represent a new drug target for addressing metabolic disorders, including NASH.

Prediction of protein-RNA interactions from single-cell transcriptomic data

Proteins are crucial in regulating every aspect of RNA life, yet understanding their interactions with coding and noncoding RNAs remains limited. Experimental studies are typically restricted to a small number of cell lines and a limited set of RNA-binding proteins (RBPs). Although computational methods based on physico-chemical principles can predict protein-RNA interactions accurately, they often lack the ability to consider cell-type-specific gene expression and the broader context of gene regulatory networks (GRNs). Here, we assess the performance of several GRN inference algorithms in predicting protein-RNA interactions from single-cell transcriptomic data, and propose a pipeline, called scRAPID (single-cell transcriptomic-based RnA Protein Interaction Detection), that integrates these methods with the catRAPID algorithm, which can identify direct physical interactions between RBPs and RNA molecules. Our approach demonstrates that RBP-RNA interactions can be predicted from single-cell transcriptomic data, with performances comparable or superior to those achieved for the well-established task of inferring transcription factor-target interactions. The incorporation of catRAPID significantly enhances the accuracy of identifying interactions, particularly with long noncoding RNAs, and enables the identification of hub RBPs and RNAs. Additionally, we show that interactions between RBPs can be detected based on their inferred RNA targets. The software is freely available at https://github.com/tartaglialabIIT/scRAPID.

Phosphorylation of the compartmentalized PKA substrate TAF15 regulates RNA-protein interactions

Spatiotemporal-controlled second messengers alter molecular interactions of central signaling nodes for ensuring physiological signal transmission. One prototypical second messenger molecule which modulates kinase signal transmission is the cyclic-adenosine monophosphate (cAMP). The main proteinogenic cellular effectors of cAMP are compartmentalized protein kinase A (PKA) complexes. Their cell-type specific compositions precisely coordinate substrate phosphorylation and proper signal propagation which is indispensable for numerous cell-type specific functions. Here we present evidence that TAF15, which is implicated in the etiology of amyotrophic lateral sclerosis, represents a novel nuclear PKA substrate. In cross-linking and immunoprecipitation experiments (iCLIP) we showed that TAF15 phosphorylation alters the binding to target transcripts related to mRNA maturation, splicing and protein-binding related functions. TAF15 appears to be one of multiple PKA substrates that undergo RNA-binding dynamics upon phosphorylation. We observed that the activation of the cAMP-PKA signaling axis caused a change in the composition of a collection of RNA species that interact with TAF15. This observation appears to be a broader principle in the regulation of molecular interactions, as we identified a significant enrichment of RNA-binding proteins within endogenous PKA complexes. We assume that phosphorylation of RNA-binding domains adds another layer of regulation to binary protein-RNAs interactions with consequences to RNA features including binding specificities, localization, abundance and composition.

Prediction of on-target and off-target activity of CRISPR-Cas13d guide RNAs using deep learning

Transcriptome engineering applications in living cells with RNA-targeting CRISPR effectors depend on accurate prediction of on-target activity and off-target avoidance. Here we design and test ~200,000 RfxCas13d guide RNAs targeting essential genes in human cells with systematically designed mismatches and insertions and deletions (indels). We find that mismatches and indels have a position- and context-dependent impact on Cas13d activity, and mismatches that result in G-U wobble pairings are better tolerated than other single-base mismatches. Using this large-scale dataset, we train a convolutional neural network that we term targeted inhibition of gene expression via gRNA design (TIGER) to predict efficacy from guide sequence and context. TIGER outperforms the existing models at predicting on-target and off-target activity on our dataset and published datasets. We show that TIGER scoring combined with specific mismatches yields the first general framework to modulate transcript expression, enabling the use of RNA-targeting CRISPRs to precisely control gene dosage.

Gene regulation during meiosis

Meiosis is essential for gamete production in all sexually reproducing organisms. It entails two successive cell divisions without DNA replication, producing haploid cells from diploid ones. This process involves complex morphological and molecular differentiation that varies across species and between sexes. Specialized genomic events like meiotic recombination and chromosome segregation are tightly regulated, including preparation for post-meiotic development. Research in model organisms, notably yeast, has shed light on the genetic and molecular aspects of meiosis and its regulation. Although mammalian meiosis research faces challenges, particularly in replicating gametogenesis in vitro, advances in genetic and genomic technologies are providing mechanistic insights. Here we review the genetics and molecular biology of meiotic gene expression control, focusing on mammals.

Spermatid perinuclear RNA-binding protein promotes UBR5-mediated proteolysis of Dicer to accelerate triple-negative breast cancer progression

Triple-negative breast cancer (TNBC) is the most lethal subtype of breast cancer with no targeted therapy. Spermatid perinuclear RNA binding protein (STRBP), a poorly characterized RNA-binding protein (RBP), has an essential role in normal spermatogenesis and sperm function, but whether and how its dysregulation contributing to cancer progression has not yet been explored. Here, we report that STRBP functions as a novel oncogene to drive TNBC progression. STRBP expression was upregulated in TNBC tissues and correlated with poor disease prognosis. Functionally, STRBP promoted TNBC cell proliferation, migration, and invasion in vitro, and enhanced xenograft tumor growth and lung colonization in mice. Mechanistically, STRBP interacted with Dicer, a core component of the microRNA biogenesis machinery, and promoted its proteasomal degradation through enhancing its interaction with E3 ubiquitin ligase UBR5. MicroRNA-sequencing analysis identified miR-200a-3p as a downstream effector of STRBP, which was regulated by Dicer and affected epithelial-mesenchymal transition. Importantly, the impaired malignant phenotypes of TNBC cells caused by STRBP depletion were largely rescued by knockdown of Dicer, and these effects were compromised by transfection of miR-200a-3p mimics. Collectively, these findings revealed a previously unrecognized oncogenic role of STRBP in TNBC progression and identified STRBP as a promising target against TNBC.

SERBP1 interacts with PARP1 and is present in PARylation-dependent protein complexes regulating splicing, cell division, and ribosome biogenesis

RNA binding proteins (RBPs) containing intrinsically disordered regions (IDRs) are present in diverse molecular complexes where they function as dynamic regulators. Their characteristics promote liquid-liquid phase separation (LLPS) and the formation of membraneless organelles such as stress granules and nucleoli. IDR-RBPs are particularly relevant in the nervous system and their dysfunction is associated with neurodegenerative diseases and brain tumor development. SERBP1 is a unique member of this group, being mostly disordered and lacking canonical RNA-binding domains. Using a proteomics approach followed by functional analysis, we defined SERBP1's interactome. We uncovered novel SERBP1 roles in splicing, cell division, and ribosomal biogenesis and showed its participation in pathological stress granules and Tau aggregates in Alzheimer's disease brains. SERBP1 preferentially interacts with other G-quadruplex (G4) binders, implicated in different stages of gene expression, suggesting that G4 binding is a critical component of SERBP1 function in different settings. Similarly, we identified important associations between SERBP1 and PARP1/polyADP-ribosylation (PARylation). SERBP1 interacts with PARP1 and its associated factors and influences PARylation. Moreover, protein complexes in which SERBP1 participates contain mostly PARylated proteins and PAR binders. Based on these results, we propose a feedback regulatory model in which SERBP1 influences PARP1 function and PARylation, while PARylation modulates SERBP1 functions and participation in regulatory complexes.